Developing Blockchain-Enabled Authentication Protocols for Securing Body Area Networks in Healthcare Applications
Due to the modern trend in reaching higher levels of miniaturization, integration of wearable systems and development of wireless technologies, Body Area Networks (BANs) have recently gained popularity in healthcare and maintenance in providing real time and personalized healthcare and medical services. However, the nature of the data that is transacted via BANs and the ease with which they can be attacked present a lot of problems to solve. This research is centered in proposing blockchain based authentication protocols specific to the requirements of the BANs used in the healthcare context. The BAN ecosystem seems suited to blockchain technology since it brings trust, privacy, and data integrity into question. The suggested protocols comprise less-weighted security operations and consensus strategies applicable to BAN constrained devices. There seems to much consideration on one's latency, scalability, power usage, and yet, security. Additionally, the study looks into smart contracts for automating the access control and achieve more integration across different devices. Through theoretical analysis and simulation, existing comprehensive evaluation shows that the above protocols are effective to resist eavesdropping, spoofing as well as data tampering. The purpose of this work will be to fill the gap between the develop blockchain technology and the need for BAN in healthcare with the goal to allow for exchange of medical data while maintaining patient confidentiality. The insights identified within the study contribute to the potential of redesigning security frames of reference for BANs and challenging uncertainty in emerging healthcare technologies.
Authors
- A. S. Anakath
- S Puvana.
Institutions
- Saveetha University (IN)
Publication Details
- Published
- 2025-05-29
- DOI
- https://doi.org/10.1109/netcrypt65877.2025.11102783
- Citations
- 1
- Primary Topic
- Wireless Body Area Networks
- Type
- article
- Field-Weighted Citation Impact
- 0.67